Java Full‑Stack Developer (Microservices, Big Data & Spark Batch)

Role Overview A highly experienced Java Full‑Stack Engineer with deep expertise in Microservices, distributed systems, and Big Data platforms. This role requires hands-on design and development of high‑throughput microservices, Spark‑based batch pipelines, and Kafka‑driven streaming workflows for large‑scale enterprise environments. Key Responsibilities Design microservices using Java, Spring Boot, Spring Cloud, and cloud‑native patterns. Build and optimize REST APIs , event‑driven components, and distributed workflows. Develop Spark batch jobs for large‑scale data processing, transformations, and aggregations. Implement Kafka streaming pipelines for real‑time ingestion and processing. Build full‑stack features using React/Angular (or client‑specified UI stack). Optimize performance of microservices and data pipelines for low latency and high throughput . Collaborate with DevOps teams to deploy services on AWS/GCP/Azure. Ensure observability, fault tolerance, and reliability across services. Lead code reviews, mentor junior engineers, and enforce engineering best practices. Technical Skills Required Java (8/11/17), Collections, Concurrency, Multithreading Spring Boot, Spring Cloud, REST, Microservices Spark (Batch + Structured Streaming) Hadoop ecosystem: Hive, HDFS, HBase, Presto (as applicable) Front‑end: React / Angular Cloud: AWS preferred (EMR, EKS, Lambda, S3, DynamoDB, Fargate) CI/CD: Jenkins, GitHub Actions, Maven/Gradle Professional Experience 10+ years of enterprise‑grade development experience. Strong experience building Spark batch pipelines for large datasets. Proven ability to design distributed, event‑driven microservices . Hands‑on experience with Kafka streaming and high‑volume ingestion. Solid understanding of system design , scalability, and performance tuning. Experience leading teams, mentoring developers, and driving architectural decisions. #J-18808-Ljbffr